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LangGraph实现智能体
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LangGraph实现智能体

Tags
AI
LLM
Published
February 24, 2025
Author
YidaHu
 

LangGraph项目

 
This is a quick start guide to help you get a LangGraph app up and running locally.
Requirements
  • Python >= 3.11

Install the LangGraph CLI

pip install --upgrade "langgraph-cli[inmem]"

🌱 Create a LangGraph App

Create a new app from the react-agent template. This template is a simple agent that can be flexibly extended to many tools.
Python ServerNode Server
langgraph new path/to/your/app --template react-agent-python
Additional Templates
If you use langgraph new without specifying a template, you will be presented with an interactive menu that will allow you to choose from a list of available templates.

Install Dependencies

In the root of your new LangGraph app, install the dependencies in edit mode so your local changes are used by the server:
pip install -e .

Create a .env file

You will find a .env.example in the root of your new LangGraph app. Create a .env file in the root of your new LangGraph app and copy the contents of the .env.example file into it, filling in the necessary API keys:
LANGSMITH_API_KEY=lsv2... TAVILY_API_KEY=tvly-... ANTHROPIC_API_KEY=sk- OPENAI_API_KEY=sk-...
Get API Keys
           

          Launch Local LangGraph Server

          🚀 Launch LangGraph Server

          langgraph dev
          This will start up the LangGraph API server locally. If this runs successfully, you should see something like:
          Ready!
          In-Memory Mode
          The langgraph dev command starts LangGraph Server in an in-memory mode. This mode is suitable for development and testing purposes. For production use, you should deploy LangGraph Server with access to a persistent storage backend.
          If you want to test your application with a persistent storage backend, you can use the langgraph up command instead of langgraph dev. You will need to have docker installed on your machine to use this command.

          LangGraph Studio Web UI

          LangGraph Studio Web is a specialized UI that you can connect to LangGraph API server to enable visualization, interaction, and debugging of your application locally. Test your graph in the LangGraph Studio Web UI by visiting the URL provided in the output of the langgraph dev command.
          LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
          Connecting to a server with a custom host/port
          If you are running the LangGraph API server with a custom host / port, you can point the Studio Web UI at it by changing the baseUrl URL param. For example, if you are running your server on port 8000, you can change the above URL to the following:
          https://smith.langchain.com/studio/baseUrl=http://127.0.0.1:8000
          Safari Compatibility
          Currently, LangGraph Studio Web does not support Safari when running a server locally.
           
           
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